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A priori testing of sparse adaptive polynomial chaos expansions using an ocean general circulation model database
This work explores the implementation of an adaptive strategy to design sparse ensembles of oceanic simulations suitable for constructing polynomial chaos surrogates. We use a recently developed pseudo-spectral algorithm that is based on a direct application of the Smolyak sparse grid formula and th...
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Published in: | Computational geosciences 2013-12, Vol.17 (6), p.899-911 |
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creator | Winokur, Justin Conrad, Patrick Sraj, Ihab Knio, Omar Srinivasan, Ashwanth Thacker, W. Carlisle Marzouk, Youssef Iskandarani, Mohamed |
description | This work explores the implementation of an adaptive strategy to design sparse ensembles of oceanic simulations suitable for constructing polynomial chaos surrogates. We use a recently developed pseudo-spectral algorithm that is based on a direct application of the Smolyak sparse grid formula and that allows the use of arbitrary admissible sparse grids. The adaptive algorithm is tested using an existing simulation database of the oceanic response to Hurricane Ivan in the Gulf of Mexico. The a priori tests demonstrate that sparse and adaptive pseudo-spectral constructions lead to substantial savings over isotropic sparse sampling in the present setting. |
doi_str_mv | 10.1007/s10596-013-9361-3 |
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subjects | Algorithms Design engineering Earth and Environmental Science Earth Sciences General circulation models Geotechnical Engineering & Applied Earth Sciences Hurricanes Hydrogeology Mathematical Modeling and Industrial Mathematics Ocean circulation Original Paper Polynomials Soil Science & Conservation Studies |
title | A priori testing of sparse adaptive polynomial chaos expansions using an ocean general circulation model database |
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